📋 JSON Parsers - CWhiting · Scour

alasdairforsythe/jsondec: Simple and high-performance JSON decoder for Go, designed for fast & easy API response parsing ✅Format Verification

github.com·3d·r/golang

From maps to bitmaps (and from bitmaps to bitmaps): A faster decision engine 📊Columnar Databases

cerbos.dev·1d·Hacker News

CRANE: Constrained Reasoning Injection for Code Agents via Nullspace Editing 🧠Context Engineering

Harness-first agentic SDLC: How OpenSearch builds software using its own search engine 💻Coding Agents

opensearch.org·7h·Hacker News

Forging a Personal Chatbot with OpenAI API, Chroma DB, HuggingFace Spaces, and Gradio 🔥 💬ChatGPT

mlops.community·1d

REST vs GraphQL vs gRPC REST, GraphQL, and gRPC are three distinct approaches to designing APIs. Each offers a different trade-off between simplicity, performan... 🔌API Development

youtube.com·3d

Realtime API ⏱️Real-time Analytics

status.openai.com

·2d

mitghi/jetro: High-performance JSON query engine for Rust (jq-like DSL with compilation & VM) 📋OpenAPI

github.com·6d·Hacker News

zSort: Stable Distribution Sort using Z-Score Partitioning 🎲Probabilistic Data Structures

vincentlaucsb/csv-parser: A modern C++ CSV parser and serializer that doesn't make you choose between ease of use or performance. 📋CSV Processing

github.com·6d·r/cpp

DIVER:Diving Deeper into Distilled Data via Expressive Semantic Recovery 🧮Vector Embeddings

Natural Language based Specification and Verification 🤖LLM

Curriculum Learning-Guided Progressive Distillation in Large Language Models 🤖Large Language Models

GraphFlash: Enabling Fast and Elastic Graph Processing on Serverless Infrastructure ☁️Serverless Databases

Chain-based Distillation for Effective Initialization of Variable-Sized Small Language Models 🧠LLMs

Safety Context Injection: Inference-Time Safety Alignment via Static Filtering and Agentic Analysis 🛡️AI Safety

Using Semantic Distance to Estimate Uncertainty in LLM-Based Code Generation 🤖LLM

Reasoning Compression with Mixed-Policy Distillation ⚡LLM Optimization

A Scalable Recipe on SuperMUC-NG Phase 2: Efficient Large-Scale Training of Language Models 🏠Local LLM Deployment

Unleashing Scalable Context Parallelism for Foundation Models Pre-Training via FCP 🏗️LLM Infrastructure

Log in to enable infinite scrolling